Interseismic slip distribution and locking characteristics of the mid-southern segment of the Tanlu fault zone

We employ the block negative dislocation model to invert the distribution of fault coupling and slip rate deficit on the different segments of the Tanlu(Tancheng-Lujiang) fault zone, according to the GPS horizontal velocity field from 1991 to 2007(the first phase) and 2013 to 2018(the second phase). By comparing the deformation characteristics results, we discuss the relationship between the deformation characteristics with the M earthquake in Japan. The results showed that the fault coupling rate of the northern section of Tancheng in the second phase reduced compared with that in the first phase. However, the results of the two phases showed that the northern section of Juxian still has a high coupling rate, a deep blocking depth, and a dextral compressive deficit, which is the enrapture section of the 1668 Tancheng earthquake. At the same time, the area strain results show that the strain rate of the central and eastern regions of the second phase is obviously enhanced compared with that of the first phase. The occurrence of the great earthquake in Japan has played a specific role in alleviating the strain accumulation in the middle and south sections of the Tanlu fault zone. The results of the maximum shear strain show that the shear strain in the middle section of the Tanlu fault zone in the second phase is weaker than that in the first phase, and the maximum shear strain in the southern section is stronger than that in the first phase. The fault coupling coefficient of the south Sihong to Jiashan section is high, and it is also the unruptured section of historical earthquakes. At the same time, small earthquakes in this area are not active and accumulate stress easily, so the future earthquake risk deserves attention.

An Enhanced Steepest Descent Method for Global Optimization-Based Mesh Smoothing

In order to speed up the global optimization-based mesh smoothing, an enhanced steepest descent method is presented in the paper. Numerical experiment results show that the method performs better than the steepest descent method in the global smoothing. We also presented a physically-based interpretation to explain why the method works better than the steepest descent method.

Three-step relaxed hybrid steepest-descent methods for variational inequalities

The classical variational inequality problem with a Lipschitzian and strongly monotone operator on a nonempty closed convex subset in a real Hilbert space is studied. A new three-step relaxed hybrid steepest-descent method for this class of variational inequalities is introduced. Strong convergence of this method is established under suitable assumptions imposed on the algorithm parameters.

Rupture model of the 2013 M_W 6.6 Lushan (China) earthquake constrained by a new GPS data set and its effects on potential seismic hazard

Vertical records are critically important when determining the rupture model of an earthquake, especially a thrust earthquake. Due to the relatively low fitness level of near-field vertical displacements, the precision of previous rupture models is relatively low, and the seismic hazard evaluated thereafter should be further updated. In this study, we applied three-component displacement records from GPS stations in and around the source region of the 2013 MW6.6 Lushan earthquake to re-investigate the rupture model.To improve the resolution of the rupture model, records from both continuous and campaign GPS stations were gathered, and secular deformations of the GPS movements were removed from the records of the campaign stations to ensure their reliability. The rupture model was derived by the steepest descent method（SDM）, which is based on a layered velocity structure. The peak slip value was about 0.75 m, with a seismic moment release of 9.89 × 1018 N·m, which was equivalent to an MW6.6 event. The inferred fault geometry coincided well with the aftershock distribution of the Lushan earthquake. Unlike previous rupture models, a secondary slip asperity existed at a shallow depth and even touched the ground surface. Based on the distribution of the co-seismic ruptures of the Lushan and Wenchuan earthquakes, post-seismic relaxation of the Wenchuan earthquake, and tectonic loading process, we proposed that the seismic hazard is quite high and still needs special attention in the seismic gap between the two earthquakes.

Convergence of Hybrid Steepest-Descent Methods for Generalized Variational Inequalities

In this paper, we consider the generalized variational inequality GVI（F, g, C）, where F and g are mappings from a Hilbert space into itself and C is the fixed point set of a nonexpansive mapping. We propose two iterative algorithms to find approximate solutions of the GVI（F,g, C）. Strong convergence results are established and applications to constrained generalized pseudo-inverse are included.

CONVERGENCE ANALYSIS OF A LOCALLY ACCELERATED PRECONDITIONED STEEPEST DESCENT METHOD FOR HERMITIAN-DEFINITE GENERALIZED EIGENVALUE PROBLEMS

By extending the classical analysis techniques due to Samokish, Faddeev and Faddee- va, and Longsine and McCormick among others, we prove the convergence of the precon- ditioned steepest descent with implicit deflation （PSD-id） method for solving Hermitian- definite generalized eigenvalue problems. Furthermore, we derive a nonasymptotie estimate of the rate of convergence of the PSD-id method. We show that with a proper choice of the shift, the indefinite shift-and-invert preconditioner is a locally accelerated preconditioner, and is asymptotically optimal which leads to superlinear convergence Numerical examples are presented to verify the theoretical results on the convergence behavior of the PSD- id method for solving ill-conditioned Hermitian-definite generalized eigenvalue problems arising from electronic structure calculations. While rigorous and full-scale convergence proofs of preconditioned block steepest descent methods in practical use still largely eludes us, we believe the theoretical results presented in this paper shed light on an improved understanding of the convergence behavior of these block methods.

Full waveform inversion with spectral conjugategradient method

Spectral conjugate gradient method is an algorithm obtained by combination of spectral gradient method and conjugate gradient method,which is characterized with global convergence and simplicity of spectral gradient method,and small storage of conjugate gradient method.Besides,the spectral conjugate gradient method was proved that the search direction at each iteration is a descent direction of objective function even without relying on any line search method.Spectral conjugate gradient method is applied to full waveform inversion for numerical tests on Marmousi model.The authors give a comparison on numerical results obtained by steepest descent method,conjugate gradient method and spectral conjugate gradient method,which shows that the spectral conjugate gradient method is superior to the other two methods.

Numerical Fitting of Planar Photographic Images with Spherical Voronoi Diagrams

There are many phenomena that generate polygonal tessellations on surfaces of 3D objects. One interesting example is the jackfruit, a multiple fruit found in the tropics. A recent study found the best-fit spherical Voronoi diagram from a photo of jackfruit skin, but the optimization was relative to the radius of the sphere and the height of the spikes. In this study, we propose a method for adjusting the position of the center of the sphere in addition to these parameters. Experiments were conducted using both ideal and real data. However, convergence with real data has not been confirmed due to relaxation of the convergence condition.

针对频率失调问题的挖掘机ANC系统优化设计

在进行窄带主动噪声控制(Narrowband Active Noise Control,NANC)过程中,常采用非声学传感器来获取参考信号,但非声学传感器会因老化和疲劳积累产生误差,使NANC系统频率失调(Frequency Mismatch,FM),导致降噪性能下降,甚至失效。针对此问题,提出一种基于自适应补偿(Adaptive Compensation,AC)的控制方案,该方案利用滤波增强信号与原始信号的相关性,设计一个频率跟踪质量评价因子,使该方案能更精准地实现对频率的追踪,以取得更优的FM补偿效果。通过仿真对比发现,与传统解决方案相比,AC方案能应对更大FM,使NANC系统具有更好的稳定性,初步验证了算法的优越性。进一步开展台架试验与实机实验,试验结果表明:当FM达到10%,经AC方案优化的NANC系统对挖掘机2、4、6阶噪声降噪量仍达到了15.2 dB、24.1 dB、21.2 dB,进一步验证了AC方案的性能。同时,也表明所提AC方案能有效实现对FM的控制,具有较高的实用价值。

基于改进Yolov5模型的纱筒余纱量检测方法

为实现针织圆纬机纱架上纱筒余纱量的实时检测,提出一种深度学习与传统图像处理相结合的检测方法。通过优化Yolov5的主干网络并加入Shuffle-Attention注意力机制,利用改进后模型在图像中检测并框出纱筒位置;然后利用透视变换、均值偏移、canny轮廓检测、闭操作等处理获取纱筒内外圆轮廓,设计基于梯度下降的圆拟合算法,拟合纱筒内外圆的轮廓,得到纱筒的内外圆半径;最后结合小孔成像的原理完成纱筒余纱量的测量。结果表明:改进后的Yolov5模型在纱筒检测精度上达到99.5%,检测速度可达20帧/s,同时模型参数减少至3.255×106可检测的最小纱筒余纱量为3 mm,当纱筒余纱量小于3 mm后,将其视为空筒,进行延时更换。本文算法拟合圆所花费时间是传统霍夫圆检测算法的1/4左右,因此可满足针织车间的实际应用需求。

基于变增益最速梯度下降法的表贴式永磁同步电机位置修正策略

滑模观测器具有响应速度快、鲁棒性强等优点,已广泛应用于表贴式永磁同步电机无位置传感器的中、高速控制系统。然而,具有固定参数的滑模观测器很难在宽速度范围内保持一致的估算精度,而采用基于速度观测器带宽限制的方法进行噪声和扰动抑制会降低电机的动态性能。针对上述问题,该文首先分析滑模观测器估算表贴式永磁同步电机转子位置的误差产生机理,提出一种新型位置误差观测器,主要思想是基于磁链观测进行位置误差连续估算,并采用最速梯度下降法对积分过程进行反馈校正;然后,通过变增益循环迭代优化提高位置误差观测器的速度与准确性;最后搭建表贴式永磁同步电机加载测试平台进行实验,结果验证了所提方法具有位置观测精度高、鲁棒性强的特点。

Soliton resolution and asymptotic stability of N-solutions for the defocusing Kundu–Eckhaus equation with nonzero boundary conditions

In this paper,we address interesting soliton resolution,asymptotic stability of N-soliton solutions and the Painleve asymptotics for the Kundu-Eckhaus(KE)equation with nonzero boundary conditions iq_(t)+q_(xx)-2(l|q|^(2)-1)q+4β^(2)(lql^(4)-1)q+4iβ(lql^(2))_(x)q=0,q(x,0)=q_(0)(x)-±1,x→±∞.The key to proving these results is to establish the formulation of a Riemann-Hilbert(RH)problem associated with the above Cauchy problem and find its connection with the RH problem of the defocusing NLS equation.With the■-steepest descent method and the results of the defocusing NLS equation,we find complete leading order approximation formulas for the defocusing KE equation on the whole(x,t)half-plane including soliton resolution and asymptotic stability of N-soliton solutions in a solitonic region,Zakharov-Shabat asymptotics in a solitonless region and the Painlevéasymptotics in two transition regions.

Fractional-order global optimal backpropagation machine trained by an improved fractional-order steepest descent method

We introduce the fractional-order global optimal backpropagation machine,which is trained by an improved fractionalorder steepest descent method(FSDM).This is a fractional-order backpropagation neural network(FBPNN),a state-of-the-art fractional-order branch of the family of backpropagation neural networks(BPNNs),different from the majority of the previous classic first-order BPNNs which are trained by the traditional first-order steepest descent method.The reverse incremental search of the proposed FBPNN is in the negative directions of the approximate fractional-order partial derivatives of the square error.First,the theoretical concept of an FBPNN trained by an improved FSDM is described mathematically.Then,the mathematical proof of fractional-order global optimal convergence,an assumption of the structure,and fractional-order multi-scale global optimization of the FBPNN are analyzed in detail.Finally,we perform three(types of)experiments to compare the performances of an FBPNN and a classic first-order BPNN,i.e.,example function approximation,fractional-order multi-scale global optimization,and comparison of global search and error fitting abilities with real data.The higher optimal search ability of an FBPNN to determine the global optimal solution is the major advantage that makes the FBPNN superior to a classic first-order BPNN.

基于非负约束的重力向下延拓BTTB-MRNSD方法

向下延拓作为处理与解释重力数据的一项重要技术,因其计算的不适定性而备受研究人员的关注。空间域延拓方法一般延拓精度较高,但通常计算复杂度较大。本文首先根据重力异常数据的特点,借鉴图像复原问题的处理思路,提出了一种重力向下延拓等效数学模型。然后,基于系数矩阵的块-托普利茨-托普利茨-块(BTTB)结构特点,本文提出了一种具有非负约束的空间-波数混合域下延迭代方法。该方法克服了空间域延拓计算复杂度大的问题,计算效率较高。基于理论重力模型和实测异常数据的对比试验表明,本文提出的重力下延方法具有相对较高的下延精度和稳定性,且收敛性较好。

航空装备缓冲气囊设计与缓冲特性研究

航空装备缓冲气囊以重量小、成本低等优势成为航空装备缓冲系统的研究热点。为快速解决航空装备缓冲气囊的设计问题,本文运用数值仿真软件,以航空装备缓冲气囊为研究对象,依据运动学、工程热力学及柔性薄壳力学等理论建立了环形缓冲气囊的数值仿真模型,利用最速下降法对模型进行优化设计;将优化参数的仿真结果与试验结果进行对比,验证模型建立的正确性,并分析不同参数(开口面积、开口压力和气囊高度)对缓冲气囊缓冲特性的影响。结果表明,当其他参数一定时,随着开口面积增加,缓冲过载减小,着地速度增加;随着开口压力增加,缓冲过载增加,着地速度减小;随着气囊高度增加,缓冲过载减小,着地速度变化不大。本文仿真方法可以迅速确定缓冲气囊的关键设计参数(如开口面积、排气压力、缓冲高度等)与外形,可以提升缓冲气囊的设计效率,为研究气囊缓冲特性提供了理论依据。

用于JPEG图像的高容量信息隐藏算法

使用JPEG图像的DCT系数作为隐藏载体,通过一种改进的量化嵌入算法提高了信息隐藏的容量.算法以基于结构相似度的图像质量指标作为图像的失真度量,以最速下降法选择嵌入算法中的控制参数,保证了数据嵌入后的图像具有较低的失真水平.实验结果表明本文提出的算法提高了信息隐藏的容量,并较好地平衡了失真和容量之间的关系.

改进的高阶收敛FastICA算法

高阶收敛的FastICA具有形式简单、收敛速度快的特点,但其对初始值的选择比较敏感,若初始值选择不当很容易影响收敛的效果,甚至造成不收敛的结果.针对这一问题,采用最速下降法对三阶和五阶收敛的FastICA算法进行改进.首先,应用最速下降法求出初值,再用高阶收敛的FastICA算法求出最优解.语音信号的分离实验表明:改进后的算法对混合信号进行了较好的分离,并且有效地克服了初值敏感性的问题.

改进人工势场法的机械臂避障路径规划

针对传统机械臂路径规划只适用于具有特殊构型的机械臂这一不足,提出在利用遗传算法等方法求解得到一组合理的关节值后,运用人工势场法在机械臂关节空间内搜索、采用合势能最速下降为控制标准的机械臂路径规划方法。同时利用在局部极小附近添加虚拟障碍,产生虚拟斥力势能的方法解决了局部极小问题,使机械臂成功绕过障碍到达目标。仿真验证了该方法的正确性和有效性。

基于无参考质量评价模型的静脉图像采集方法

由于不同人的手背静脉属性间存在较大差异,因此对于不同静脉对象,在固定采集系统参数条件下很难都采集到高质量的静脉图像,这里提出了一种针对静脉特点的质量评价模型,并设计了基于评价结果的自寻优静脉图像采集方法.首先,提出了基于关键信息熵的测度函数,衡量了静脉信息的完整性;其次,提出了基于轮廓波分解的测度函数,用于评价静脉方向性信息的丰富性;再次,将两种测度函数融合,构成了客观的无参考的质量评价模型;最后,在图像自寻优过程中,提出了迭代淘汰机制,克服了最速下降法在寻优过程易陷入局部最优的缺陷.实验表明,提出的质量评价模型是可控的,且满足人眼视觉系统的视觉特性,同时,通过提出的迭代淘汰机制,降低了寻优过程的迭代次数,保证了采集系统的实时性要求.

几种优化方法在频率域全波形反演中的应用效果及对比分析研究

全波形反演方法是一个有效求解参数重建问题的方法,其本质是一个寻找最优解的优化问题,目前多用局部最优方法求解,如最速下降法、共轭梯度法、高斯-牛顿法、拟牛顿法等.文中给出了常用的优化方法,基于二维声波方程,将这些方法应用于部分overthrust模型的反演,通过对各方法所得反演模型的精度和计算时间的对比分析,对各个方法的优缺点进行总结,为后续多参数反演或高维方程参数反演提供方法选择上的参考;针对所要求解的反问题,选用的优化方法需要在收敛速率、计算存储量和算法的稳定性之间进行权衡,以得到一个最优的反演结果.